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Filters: Keyword is Polymorphism, Single Nucleotide and Author is Rich, Stephen S [Clear All Filters]

2020

Zhao X, Qiao D, Yang C, Kasela S, Kim W, Ma Y, Shrine N, Batini C, Sofer T, Taliun SAGagliano, et al. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants. Nat Commun. 2020 ;11(1):5182.

2021

Mikhaylova AV, McHugh CP, Polfus LM, Raffield LM, Boorgula MPreethi, Blackwell TW, Brody JA, Broome J, Chami N, Chen M-H, et al. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program. Am J Hum Genet. 2021 ;108(10):1836-1851.

2022

Thibord F, Klarin D, Brody JA, Chen M-H, Levin MG, Chasman DI, Goode EL, Hveem K, Teder-Laving M, Martinez-Perez A, et al. Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors. Circulation. 2022 ;146(16):1225-1242.

Mahajan A, Spracklen CN, Zhang W, C Y Ng M, Petty LE, Kitajima H, Yu GZ, Rüeger S, Speidel L, Kim YJin, et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat Genet. 2022 ;54(5):560-572.

Elgart M, Lyons G, Romero-Brufau S, Kurniansyah N, Brody JA, Guo X, Lin HJ, Raffield L, Gao Y, Chen H, et al. Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations. Commun Biol. 2022 ;5(1):856.

Hindy G, Dornbos P, Chaffin MD, Liu DJ, Wang M, Selvaraj MSunitha, Zhang D, Park J, Aguilar-Salinas CA, Antonacci-Fulton L, et al. Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. Am J Hum Genet. 2022 ;109(1):81-96.

DiCorpo D, Gaynor SM, Russell EM, Westerman KE, Raffield LM, Majarian TD, Wu P, Sarnowski C, Highland HM, Jackson A, et al. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. Commun Biol. 2022 ;5(1):756.

2023

Chen F, Wang X, Jang S-K, Quach BC, J Weissenkampen D, Khunsriraksakul C, Yang L, Sauteraud R, Albert CM, Allred NDD, et al. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. Nat Genet. 2023 ;55(2):291-300.

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